Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add skills/geezerrrr/motive/model-usagenpx skills add geezerrrr/motive --skill model-usagegit clone --depth 1 https://github.com/geezerrrr/motiveWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/geezerrrr/motive/model-usage)<a href="https://agentmods.dev/skills/geezerrrr/motive/model-usage"><img src="https://agentmods.dev/badge/skills/geezerrrr/motive/model-usage.svg" alt="Measured on agentmods" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5 | $0.00069 | $0.00563 |
| Opus 5 | $0.00034 | $0.00282 |
| Sonnet 5 | $0.00014 | $0.00113 |
| Haiku 4.5 | $0.00007 | $0.00056 |
Grade A, and why
model-usage scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 4d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
This is a copy
94% identical to model-usage — 2 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
What it actually says
Model usage
Overview
Get per-model usage cost from CodexBar's local cost logs. Supports "current model" (most recent daily entry) or "all models" summaries for Codex or Claude.
TODO: add Linux CLI support guidance once CodexBar CLI install path is documented for Linux.
Quick start
- Fetch cost JSON via CodexBar CLI or pass a JSON file.
- Use the bundled script to summarize by model.
python {baseDir}/scripts/model_usage.py --provider codex --mode current
python {baseDir}/scripts/model_usage.py --provider codex --mode all
python {baseDir}/scripts/model_usage.py --provider claude --mode all --format json --pretty
Current model logic
- Uses the most recent daily row with
modelBreakdowns. - Picks the model with the highest cost in that row.
- Falls back to the last entry in
modelsUsedwhen breakdowns are missing. - Override with
--model <name>when you need a specific model.
Inputs
- Default: runs
codexbar cost --format json --provider <codex|claude>. - File or stdin:
codexbar cost --provider codex --format json > /tmp/cost.json
python {baseDir}/scripts/model_usage.py --input /tmp/cost.json --mode all
cat /tmp/cost.json | python {baseDir}/scripts/model_usage.py --input - --mode current
Output
- Text (default) or JSON (
--format json --pretty). - Values are cost-only per model; tokens are not split by model in CodexBar output.
References
- Read
references/codexbar-cli.mdfor CLI flags and cost JSON fields.
What ships with it
2 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 4d ago First seen · 70 lines · 69 tokens per session scan A b88045ef1c5c
model-usage is a skill published in the GitHub repository geezerrrr/motive (117 stars, last pushed 6mo ago), licensed MIT. It adds 69 tokens to every session and 563 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. It is 94% identical to model-usage, differing in 2 lines, and is treated as a copy.
Other skills, from other repositories
engram-rebuild
이미 설치된 engram 환경에 개발 변경을 적용한다. dev-rebuild.ps1 로 충분한지 INSTALL.ps1 전체를 돌려야 하는지 판단하고 실행한다. 트리거 — 재빌드, 리빌드, dev 변경 적용, 설치본에 반영, overlay 재시작, exe 갱신, "고친 거 확인하려면 뭐 돌려야 해", rebuild, redeploy.
orchestrate
Run Engram's Orchestrator-Planner-Coder-Servant workflow for multi-step development, refactors, or research-plus-implementation tasks that need an acceptance contract and independent verification. Trigger for "orchestrate", delegation requests, planning then implementation, or complex multi-step development. Do not…
engram-new-session
Skill "engram-new-session" from JJHbrams/Project-AMBER, covering engram 말풍선 — 새 세션 시작, 실행 절차 and 규칙.
issue-maintenance
Periodic and on-demand maintenance pass over a repo's open GitHub issue backlog. Re-labels miscategorized or unlabeled issues (bug/enhancement/question/invalid/duplicate) and bug lifecycle labels (needs-repro/needs-info) following the same decision logic as Anthropic's own dogfooded triage-issue command; re-scores…
evidence-check
An honesty gate that makes an AI back up its claims with real evidence instead of presenting guesses as fact. Use as an always-on background behavior, and invoke explicitly when the user says show your work, prove it, how do you know that, evidence check, what's your source, back that up, or when the AI is…
comment-reaper
Finds and removes unnecessary code comments - the ones that restate the code, cite an issue number, narrate refactor history, or wrap a one-line function in six lines of JSDoc. Sorts every find into auto-fix, propose, or never-touch, so the WHY comments survive the sweep. Trigger on: "comment reaper", "reap comments"…